The main purpose of this article is to gain an insight into the relationships between variables describing the environmental conditions of the Far Northern section of the Great Barrier Reef, Australia, Several of the variables describing these conditions had different measurement levels and often they had non-linear relationships. Using non-linear principal component analysis, it was possible to acquire an insight into these relationships. Furthermore. three geographical areas with unique environmental characteristics could be identified. Copyright (c) 2005 John Wiley & Sons, Ltd
In many physical geography settings, principal component analysis (PCA) is applied without consider...
In the framework of model complexity reduction, we investigate the ability of the principal componen...
The objectives of this preliminary study are to determine heavy metal concentration in mangrove estu...
The main purpose of this article is to gain an insight into the relationships between variables desc...
Identification of the key environmental indicators (KEIs) from a large number of environmental varia...
This paper introduces a new technique in ecology to analyze spatial and temporal variability in envi...
In many large environmental datasets redundant variables can be discarded without the loss of extra ...
A nonlinear generalisation of Principal Component Analysis (PCA), denoted Nonlinear Principal Compo...
<p>Points are coded by water depth as either deep (filled symbols) or surface (open symbols) and by ...
In many physical geography settings, principal component analysis (PCA) is applied without considera...
<p>Principal component analysis normalized environmental data from stations along the Ellett Line tr...
<p>The first two principal component axes are displayed. Sites are coded according to: (a) the areal...
International audienceComplex principal component analysis (CPCA) is a useful linear method for dime...
PCA of Chl a, meteorological and hydrological data for the 2015 data set (A) and 2016 data set (B). ...
This paper demonstrates how the results from different methods can be interpreted on the basis of a ...
In many physical geography settings, principal component analysis (PCA) is applied without consider...
In the framework of model complexity reduction, we investigate the ability of the principal componen...
The objectives of this preliminary study are to determine heavy metal concentration in mangrove estu...
The main purpose of this article is to gain an insight into the relationships between variables desc...
Identification of the key environmental indicators (KEIs) from a large number of environmental varia...
This paper introduces a new technique in ecology to analyze spatial and temporal variability in envi...
In many large environmental datasets redundant variables can be discarded without the loss of extra ...
A nonlinear generalisation of Principal Component Analysis (PCA), denoted Nonlinear Principal Compo...
<p>Points are coded by water depth as either deep (filled symbols) or surface (open symbols) and by ...
In many physical geography settings, principal component analysis (PCA) is applied without considera...
<p>Principal component analysis normalized environmental data from stations along the Ellett Line tr...
<p>The first two principal component axes are displayed. Sites are coded according to: (a) the areal...
International audienceComplex principal component analysis (CPCA) is a useful linear method for dime...
PCA of Chl a, meteorological and hydrological data for the 2015 data set (A) and 2016 data set (B). ...
This paper demonstrates how the results from different methods can be interpreted on the basis of a ...
In many physical geography settings, principal component analysis (PCA) is applied without consider...
In the framework of model complexity reduction, we investigate the ability of the principal componen...
The objectives of this preliminary study are to determine heavy metal concentration in mangrove estu...